Voxel is a basic picture element for composing 3D images. Since the generation of each voxel involves at least four pixels from four different view images for the case of full parallax 3D images, any voxel can be generated if the pixel pattern can be found. To find the pixel pattern, a set of voxels with known coordinated values are created by an optical geometry of the point light source array based 3D imaging system. This geometry provides that voxels aligned in planes parallel to the point light source array plane. The pixel pattern corresponding to each voxel is determined as the passage of seeing the point light sources related with the voxel, in the viewing zone. The resulting pixel patterns creates a good 3D image.

Conventional integral imaging systems utilize lenslet arrays with fixed focal lengths and aperture sizes. A time-multiplexing method, called a moving array-lens technique, improves the viewing resolution because the Nyquist sampling resolution limit imposed by a periodic lenslet array can be overcome. In the moving array-lenslet technique, if lenslet arrays with a low fill factor are used, the viewing angle can also be improved without degrading the viewing resoluton seriously. We show that the product of depth and resolution square of the displayed three-dimensional image is limited by the inverse of the illumination wavelength in conventional integral imaging systems. This means that the longitudinal depth of three-dimensional images can be improved only by sacrificing the resolution. Therefore, to enhance both the longitudinal depth and the resolution of a three-dimensional image, we discuss the use of an array of lenslets with different focal lengths and aperture sizes. The required lenslet parameters for our method are calculated. Our theoretical analysis indicates that significant improvements in longitudinal depth and resolution can be obtained using the nonuniform lenslet array and the time-multiplexing technique.

The quality of the reconstructed three-dimensional (3D) object in a correlation-based optical reconstruction of three-dimensional object is numerically evaluated. An original 3D object is encrypted by using a random phase mask located in the Fourier plane, and then the encrypted pattern is recorded as an encrypted digital hologram together with a reference plane wave. The key digital hologram is also recorded as an interference pattern between the Fourier transformed pattern of the random phase mask and the reference wave. Both the encrypted digital hologram and the key digital hologram are transmitted to a receiver through a communication data channel. At the receiver, the 3D scene is reconstructed in a correlation-based retrieval system. For a real-time operation of the system, a key device is an optically-addressed spatial light modulator (OA-SLM) that records a joint power spectrum between the encrypted and the key holograms. We investigate the influence of quantization of joint power spectrum in an OA-SLM on the quality of the reconstructed image. Numerical and experimental results are presented.

This paper describes a device for 3D profile measurement systems which are based on grating projection method using phase shifting technique. As a key component to these systems, we propose to apply a liquid crystal (LC) grating instead of a conventional ruled grating which has difficulty in speedy and accurate shifting of the projected pattern. This LC grating consists of 960 lines of stripe pattern on the substrate of 60×40 mm² in size and has such features as 8 bits of gray levels in dynamic range in mono-chromatic usage. A sinusoidal pattern as well as a binary pattern is realized by combining pulse width modulation control (PWMC) and frame ratio control (FRC) technique. The period of the pattern is arbitrarily controlled and, in addition, shifting of the projected pattern is also electrically realized. We demonstrate a few examples measured by the system which has this LC grating built in.

An imaging system with a focusing mechanism based on perfect projection was devised using a varifocal mirror to achieve high-quality three-dimensional imaging and precise measurement of shape. We treated two types of projection that were used as an analytical model for machine vision. First, an imaging system based on perspective projection was constructed so that the varifocal mirror was placed at the front focal point of the image taking lens. Magnification was exactly equal to the ratio of the focal length and an object point distance from the front focal point of the lens, which was fixed when focusing with the varifocal mirror. The surface shape of a spherical dent (3.5 mm in diameter) was precisely measured with the shape-from-focus-method because the dent could be viewed from the side. Second, we constructed an imaging system with a focus mechanism based on orthographic projection so that the varifocal mirror could be placed at the back focal point. The system was able to be focused on any object point at constant magnification. Taking advantage of parallel projection, an entirely focused 3-D image of a screw thread (2 mm in diameter) and its profile could successfully be obtained using the shape-from-focus method.

In this paper, an incoherent holographic 3D imaging and display system usinga modified triangular interferometer is implemented and demonstrated. The incoherent holographic system based-on this modified triangular interferometer employs the superposition of Fresnel zone patterns in which the positions and intensities of the object points are uniquely encoded and from this system the complex holograms without bias and conjugate image for 3D object can be obtained. That is, the light reflected from a 3D object is divided into two beams by a beam splitter and input to the modified triangular interferometer. All patterns of two optical wave that travel the modified triangular interferometer in the clockwise and counterclockwise directions is detected by the CCD camera. Here, four pairs of interference pattern are detected by controlling combination of the waveplates in the modified interferometer system then, a complex hologram pattern without bias and conjugated image can be obtained through the modification process of these four patterns. The Mach-Zehnder interferometer is also employed, in this paper, to reconstruct this complex hologram. The real and imaginary parts of the complex hologram are placed in the upper and the lower arms of the interferometer. The Mach Zehnder intrferometer is used to reconstruct the comeplx hologram. That is, the real and imaginayr parts of a complex hologram are placed in each arm of the interferometer, respectively. And illuminating them coherently and recombining the light passed throught eh transparenceis bytheuse of the beam splitter allows the complex addition to be performed. Then, the desired 3D image is reconstructed through Fresnel diffraction, in which the panel plays a role of a holographic optical element. From some experiments with 3D object of "dies", it is suggested that a practical incoherent holographic 3D imaging and display system using a modifeid triangular interferometer can be implemented, in which the bias and conjugate image problems are alleviated.

Integral imaging, which used to be called integral photography, has been recently attracting great attention due to its possibility for dynamic color autostereoscopy with full parallax and without any use of special glasses. For its practical use, the scaling of integral imaging is a very important issue because different systems have different lens characteristics such as lens sizes and focal lengths. In this paper, we discuss the guiding rules in scaling of integral imaging. We discuss the generalized analysis on scaling and propose the simple-scaling and ratio-conserving scaling. Experimental result will also be provided.

Three-dimensional display systems through secure data communication by use of conventional or digital holograms are presented. Holographic data storage is a promising method for a huge amount of data storage with data encryption. We present a secure data communication technique by use of encrypted data read out from a secure holographic memory system. We also present a secure two-dimensional display by use of the encrypted digital holograms. Numerical and experimental verification of both systems are presented.

The fractional Fourier transform, (FRT), is a generalisation of the Fourier transform which allows domains of mixed spatial frequency and spatial information to be examined. A number of method have recently been proposed in the literature for the encryption of two dimensional information using optical systems based on the FRT. Typically, these methods require random phase screen keys to decrypt the data, which must be stored at the receiver and must be carefully aligned with the received encrypted data. We have proposed a new technique based on a random shifting or Jigsaw transformation. This method does not require the use of phase keys. The image is encrypted by juxtaposition of sections of the image in various FRT domains. The new method has been compared numerically with existing methods and shows comparable or superior robustness to blind decryption. An optical implementation is also proposed and the sensitivity of the various encryption keys to blind decryption is quantified. We also present a second image encryption technique, which is based on a recently proposed method of optical phase retrieval using the optical FRT and one of its discrete counterparts. Numerical simulations of the new algorithm indicates that the sensitivity of the keys is much greater than any of the techniques currently available. In fact the sensitivity appears to be so high that optical implementation, based on existing optical signal processing technology, may be impossible. However, the technique has been shown to be a powerful method of 2-D image data encryption.

Fingerprint verification for smart card holders is one of the methods which are able to identify smart card holders with a high level of security. However, an ingenious implementation is needed to execute it in the embedded processor quickly and safely, because of its computational burden and the limitation of the smart card performance. For this purpose, we propose a hybrid method which is a combination of personal identification number (PIN) verification with a smart card and an optical fingerprint verification method. The result of a preliminary computer simulation to evaluate the proposed system shows that false acceptance rate is completely zero, though false rejection rate is a little inferior to the conventional figerprint verification system.

A digital watermark is a visible, or preferably invisible, identification code that is permanently embedded in some digital data to prove owner authentication and provide protection of that document. In this paper we utilize a watermark generation technique based on the use of chaotic functions and the motivation for using these functions is presented. The technique used for watermark embedding is also described, together with a watermark detection scheme based on an optical Matched Filter correlator. We provide results of optical simulations of the watermark detection scheme and show that correlation-based detection is an excellent method for detecting chaotically-generated watermarks embedded in the Fourier domain using multiplicative embedding. We also show that it is possible to detect chaotically-generated watermarks in images that have been subjected to noise.

In this paper, we implement a fully phase encrypted memory system using cascaded extended fractional Fourier transform (FRT). We encrypt and decrypt a two-dimensional image obtained from an amplitude image. The fully phase image to be encrypted is fractional Fourier transformed three times and random phase masks are placed in the two intermediate planes. Performing the FRT three times increases the key size, at an added complexity of one more lens. The encrypted image is holographically recorded in a photorefractive crystal and is then decrypted by generating through phase conjugation, conjugate of encrypted image. The decrypted phase image is converted into an amplitude image by using phase contrast technique. A lithium niobate crystal has been used as a phase contrast filter to reconstruct the phase image, alleviating the need of alignment in the Fourier plane, thereby making the system rugged.

Dyadic displacements of an image can be regarded as a special type of permutations of pixel addresses. This property can be used to encrypt an image without information loss, damage, or addition. In this paper, a new optical image encryption technique based on dyadic permutations and holographic interference is proposed. First, we adopt holographic interference to record both the phase and amplitude of the Fourier transform of an input image as the intensity information. Then the recorded phase is processed through dyadic permutations based on exclusive-OR (XOR) operations. The original image can be successfully recovered by using the inverse procedure.

A new kind of computer-generated hologram termed digital correlation hologram (DCH) has been developed and demonstrated with promising results. This hologram is composed of two separated sub-holograms. The reconstructed image is obtained as a result of a spatial correlation between the hologram's two parts. The DCH codes two complex functions generated by an iterative optimization procedure while the correlation between the two sub-holograms is implemented on a joint transform correlator (JTC). When the double-elements hologram is displayed on the JTC input plane, and illuminated by a plane wave, a desired image is constructed on part of the correlator output plane. The DCH can be used for security and encryption systems, as the desired image will be received in the output plane only when the two specific sub-holograms are placed at the input plane of the JTC. Simulation and experimental result demonstrate the suggested technique.

Face recognition based on principal component analysis (PCA) using eigenfaces is popular in face recognition markets. In this paper we present a comparison between various optoelectronic face recognition techniques and principal component analysis (PCA) based technique for face recognition. Computer simulations are used to study the effectiveness of PCA based technique especially for facial images with a high level of distortion. Results are then compared to various distortion-invariant optoelectronic face recognition algorithms such as synthetic discriminant functions (SDF), projection-slice SDF, optical correlator based neural networks, and pose estimation based correlation.

Spatial light modulators are of growing interest not only for optical correlators but also for new optical measurement and processing methods. We present different applications of dynamic phase holograms based on liquid crystal elements in the field of optical measurement and manipulation. Within digital holography, modern modulators can be used in order to test the geometry as well as the behavior of objects under external load. A direct comparison between the test objects and a master object at different locations around the world is possible. Holographic tweezers are used in order to position small particles in three dimensions and to measure very small forces. We also present results of novel methods for testing aspheric surfaces and the application of dynamic hologram reconstructions for the ablation of complex patterns on the microscopic scale.

We propose an optoelectronic arbitrary radar waveform generator. It permits to generate predefined electrical waveforms according to radar specifications by driving phase and amplitude distributions of optically carried microwave signals. The control of amplitudes and phases of each radar spectrum frequency component is optically achieved by spatial light modulators (SLM). We present and experimentally demonstrate two ways to achieve the kilohertz high resolution between the frequency components of a radar signal at 7.1 GHz central frequency.

Linear filtering methods often fail to detect dark objects because the correlation peak height is proportional to the object intensity. And the high response from very bright clutter can result in false detections. In real world situations, intensity variations of targets occur. We address the problem of image recognition in the presence of unknown uniform and nonuniform intensity transformations. The uniform intensity transformations considered are multiplicative and additive. This part of the problem has already been solved using a method that we recently proposed called the LACIF (Locally Adaptive Contrast-Invariant Filter). In this paper we generalize this method for situations where a linear intensity gradient across an object can be present. For this we use a set of four orthonormal images, compute the correlations between each of those images and the scene. Then we do one more correlation and combine the fives correlation planes in a nonlinear manner. Results show that discrimination is good.

An optimum training process using a direct binary search algorithm for synthesising a spatial domain binary filter to implement in the joint transform correlator (JTC) architecture is presented. The major advantage of the proposed filter are rotation invariance, higher discriminability for similar targets, and convenience for optical implementation in the JTC using a Ferroelectric over silicon SLM as a binary phase modulator. Results of the invariant filter are presented for classical JTC, DC free JTC using phase shifting technique, and for the binarised JTC by applying edge-enhancement and mean thresholding at the JPS. Testing so far, shows that binary filter is able to distinguish between target and anti-target images for all these cases.

Conventional optical image verification systems based on the joint transform correlator (JTC) can only recover symmetric images in the output plane, which is an limitation to practical usage. In this paper, an optical asymmetric-image verification system based on the JTC is proposed. An additional phase mask is attached with a spatial light modulator (SLM), which displays the joint power spectrum as the amplitude information, to enable the reconstruction of an asymmetric image in the output plane. Two phase functions are paired and iteratively retrieved by the use of the projection onto constraint sets algorithm. One key is one of the joint functions in the input plane and acts as the key. The other phase is attached by the SLM. Compared with the image verification system based on the JTC architecture, the proposed system can obtain the asymmetric images in the output plane. In addition, the the proposed architecture can also yield the better image quality for symmetric images. Simulation results are given to verify the proposed method.

Recently, the integral imaging, which was mainly intended to pick up and display three-dimensional images, has been applied to the acquisition of the three-dimensional information of an object by several research groups. The use of a lens array and a single camera is attractive because of the simple structure. But, the elemental images that are picked up by the lens array has some degree of redundancy and the perspective angle is limited compared with the multi-camera method. In this paper, we concentrate on the acquisition of the three-dimensional information of the object by the three methods (using a lens array, using lens array and elemental image modification and using multiple cameras) and compare them in the aspects of the ambiguity, precision and quantization error.

We propose a new technique for three-dimensional (3D) target recognition using the phase information from a Fourier transform profilometer (FTP). Instead of cross-correlating the 3D target/nontargets-induced distorted grating patterns or the associated phase differences directly, the phase information are rather utilized to synthesize two complex harmonic functions, spatial frequency distributions of which are proportional to the computed profilometric phase maps of the target and the nontargets and hence to respective shape information. These complex harmonic functions due to the target and the nontargets are cross-correlated to produce highest correlation peak at the target location and almost no correlation peak for others. The feasibility of the technique is demonstrated by detailed simulations and experiments showing an excellent discrimination capability for 3D target recognition.

We introduce a single channel color nonlinear pattern recognition method. Usually, for color pattern recognition methods, the color are processed and finally its correlation outputs are combined. This is the definition of the common multichannel method. We take the input and reference scenes and we decompose them into their red, green and blue channels to obtain an amplitude and phase distribution. In this paper we study the correlations for highly noisy input iamges. These results are obtained by means of the sliced orthogonal nonlinear generalized correlation which detects the target with high discrimination capability in cases where other methods do not succeed.

We propose two lossy data compression techniques for complex-valued digital holograms of three-dimensional objects. The techniques employ unsupervised artificial neural networks to nonuniformly quantize the real and imaginary values of digital holograms. The digital holograms of real-world three-dimensional objects were captured using phase-shift interferometry. Our techniques are compared experimentally with the uniform quantization approach, and with an alternative nonuniform quantization technique based on the k-means clustering algorithm.

Surface plasmon resonance based optical sensors can be realized in integrated planar optical system on a glass substrate using mirrors and diffractive optical elements etched on the surfaces. Such a realization gives new capabilities for interrogating the sensor and for enhancing the response through multiple interactions and new possibilities for all-optical processing of the optical signals in the sensor.

It is well known that for 1D signals, a dispersion relation or Hilbert transform can be written between the magnitude and phase of a bandlimited function, provided it satisfies the so-called minimum phase condition. This condition requires that the complex zeros of the bandlimited function lie in only one half of the complex plane. When this is not the case the Hilbert transform generates the incorrect phase. Extending this concept for two and higher dimensional signals is of great practical interest but has been limited by the fundamental differences that exist between the properties of one and higher dimensional entire functions. We examine these difference and identify some classes of properties that 2D functions should satisfy, in order to possess minimum phase properties.

In many applications of optical imaging or diffraction scattering (ultrasounds or microwave), one of the main mathematical part of the inversion, problems, when linearized, become a Fourier synthesis (FS) one. This problem consists in estimating a multivariable function from the measured data which correspond to partial knowledge of its Fourier transform (FT). Most classical methods of inversion are based on interpolation of the data and fast inverse FT. But, when the data do not fill uniformly the Fourier domain or when the phase of the signal is lacking as in optical interferometry, the result obtained by such methods are not satisfactory, because these inverse problems are ill-posed. The Bayesian estimation approach, via an appropriate modeling of the unknowns gives the possibility of compensating the lack of information in the data, thus giving satisfactory results. In this paper we give an example of FS problem in an interferometry imaging.

In this work we present a generalization to complex transmittance objects of the Jared-Ennis algorithm for the generation of Synthetic Discriminant Function filters (SDFs). The original algorithm consists of the resolution of a nonlinear system of equations by means of an iterative procedure, including a phase adaptation of the filter. The method shown here takes into account the modulation of liquid crystal displays (LCD) both for scene and filter, generalizing the problem to the complex plane. Considering this new method gives a more realistic picture as the LCD modulation gives a complex distribution of the scenes instead of only real values as considered before. For instance, we use a high contrast configuration to display the scenes. Moreover, the addition of new parameters to the problem allows us to consider filters other than the phase-only one. In our case, we use a phase-mostly configuration to display the filter and the metric optimized is the maximum correlation intensity, as in the original method. Simulated results are presented for a two-class problem, as well as experimental results obtained in a VanderLugt correlator. The filters produce the desired correlation response in both cases.

In this paper we present an unwrapping weighted algorithm to analyze phase maps obtained by fringe projection 3-D profilometry. Phase unwrapping is a critical step in any phase measurement technique in which the height of an object is obtained from phase data. Indeed, when a complex object is measured, abrupt and irregular changes in the measured surface may result in local shadows. In shadow areas the observed phase data are uncertain or misleading. These zones yield “lacunae”, in the reconstruction of the 3D model. In this work we propose a new phase unwrapping method able to mitigate the “lacunae” problem by interpolation of phase data. The case of an image containing regions without phase information is treated, in our algorithm in the following manner: (a) phase inconsistencies are handled by excluding invalid pixels from the unwrapping process though the assignment of zero-valued weights; (b) an unwrapped phase map is obtained by an algorithm based on robust, path-independent method of phase unwrapping; (c) the lacks (zones of phase inconsistencies) are eliminated by means of an suitable procedure of interpolation; (d) a rewrapping procedure is used to obtain wrapped phase map without initial inconsistencies; (e) a new unwrapped phase map is obtained by the same algorithm used in step-b but with weights different from zero. The robustness of the proposed phase-unwrapping method is then tested computationally and experimentally and its enhancement is proven through the simulation and experimental results.

Hyperspectral image processing techniques are utilized for a variety of applications from geological surveys to detection of camouflaged enemy vehicles. One of the persistent problems is that huge amounts of data must be processed, since a hundred or more frequency bands of spectral information can make up a typical hyperspectral image cube. If real time processing is necessary, as in target tracking or identification, some means of selecting which bands are relevant to the image and which bands can be safely ignored is desirable. We propose a fast, easily trainable neural network filter architecture that can rapidly screen a hyperspectral image cube in near real time. A bank of filters, operating in parallel, is used to screen an image for suspected targets. Performance on simulated and real images is compared to existing recognition techniques and results in considerable reduction in overall image processing time and greater accuracy.

We present here a novel architecture for a multi-technology field programmabler gate array (MT-FPGA). Implemented with a conventional CMOS VLSI technology the architecture is suitable for prototyping photonic information processing systems. We report here that this new FPGA architecture will enable the design of reconfigurable systems that incorporate technologies outside the traditional electronic domain.

We present her a user programmable photoreceiver block that is monolithically integrated in a new generation of multi-technology field programmable gate array (MT-FPGA). Implemented with a photonic VLSI technology the device is suitable for prototyping photonic information processing systems. We also report here on the photoreceiver design methodology in a mixed signal environment and simulation results indicating the device performance.

Parallel optical interconnections which replace metallic transmission lines with optical fibers or free space channels pro-vide high throughput, easy system integration, and low latency. These systems are used in making multiprocessor based supercomputers, telecommunication exchange switches and terminals, optical information processors and computers. A first-order model for the decrease in coupling efficiency between elements of two linear arrays of a free-space, parallel optical interconnect owing to misalignments or offsets in packaging is developed. Such an array interconnect consists of an array of optical sources, such as, optical fibers or VCSELs and an array of photo-receptors, such as, optical fibers, micromirrors or photodetectors. The coupling efficiency between source and receptor elements is modeled in terms of the sizes of the array elements, inter-element spacing and distances. The coupling efficiency is subject to degrading in-fluence of six varieties of random offsets, which may occur during the alignment, and fixing of the two arrays in a pack-age. We then determine first order approximations of the effects of these offsets. Our paper presents simple analytical formulas useful for a quick design of array-based parallel optical system packages and estimation of overall system per-formances. The formulas developed are useful for design and packaging of any optoelectronic processing system.

Optical shadow-casting (OSC) technique is seriously being considered as an efficient method that is capable of optically implementing two-operand parallel logic gates and array logic systems. The sixteen logic functions for two binary patterns (variables) are optically realizable in parallel by properly configuring an array of 2×2 light emitting diodes. In this paper, we propose an enhanced OSC technique for implementing four-operand parallel logic gates. The proposed system is capable of performing 2¹⁶ logic functions by simply programming the switching mode of an array of 4×4 light emitting diodes in the input plane. This leads to an efficient and compact realization scheme when compared to the conventional two-operand OSC system.

A new multi-technology FPGA (MT-FPGA) architecture has recently been proposed. This new class of programmable hardware allows for the incorporation of a variety of multi-technology blocks like the optical sensor block as described in this paper. Using MT-FPGA technology, a system designer can readily implement any prototype multi-technology system with (1) logic parts in programmable section of MT-FPGA and (2) Multi-technology components by incorporating different multi-technology blocks from standard library. Thus, our new class of multi-technology FPGA will extend the benefits of rapid prototyping, re-configurability and evolvable hardware to multi-technology environments/applications that currently do not benefit from the advantages of programmable hardware. This paper highlights the use of an MT-FPGA chip through the implementation and evaluation of an optical power meter block. This mixed technology block is designed for implementation using a 0.35 micron CMOS process and consists of a p-diffusion to n-well photodetector followed by a wide-swing variable gain differential amplifier and a 4 bit FLASH ADC. The amplifier gain characteristics are adjustable by two analog control signals. One adjusts the gain and the other controls the biasing conditions of the differential amplifier. The last stage of the system is a 4 bit ADC that has a worst case resolution of 0.5 mV.

A three-step modified signed-digit (MSD) adder is proposed which can be optically implmented using binary logic gates. The proposed scheme depends on encoding each MSD digits into a pair of binary digits using a two-state and multi-position based encoding scheme. The design algorithm depends on constructing the addition truth table of binary-coded MSD numbers and then using Karnaugh map to achieve output minimization. The functions associated with the optical binary logic gates are achieved by simply programming the decoding masks of an optical shadow-casting logic system.

In this paper two architectures for optical image verification are roposed. Both architectures are modified from conventional joint transform correlators (JTCs) and can significantly improve the recovered image quality. First, an input phase-only function is Fourier transformed and then is interfered with a reference wave that is diffracted from a plane wave incident on another random phase mask. Second, two phase-only functions are placed at the two input sides of a beam splitter such that the interference patternof their Fourier transforms can be detected. The intensity of the interference pattern in both architectures can be recorded and then its Fourier-transform can be obtained in the output plane. To obtain a predefined target image in the output plane, the input phase function is iteratively retrieved by the use of the projection onto constraint sets algorithm. Simulation results show that the less mean squared error and better image quality are obtained for both the binary and grayscale images.

Systems for automatic pattern recognition can be performed by Artificial Neural Networks and Optical Correlators. Here, we present the design and implementation of a scheme which takes the advantages of both systems to develop an hybrid opto-digital processor, with applications in character recognition. The implementation of this system is based in the Hopfield inner products model using a Joint Transform Correlator. The procedure of recognition has the following steps: since a correlation peak is proportional to the inner product, the Hopfield method computes the inner product of the input and each memory using the Hybrid Opto-Digital Joint Transform Correlator. The second step performs a multiplication between the inner product and its respective memory, all this scaled images are added to get the future state of the input. The associative memory is replaced by two images with information of all images in the memory, this memories are added in the last step. The signal output is threshold and feedback as an input for the next iteration. The process stops when the output image does not change in the next iteration. The final image corresponds to the closest image in the memory of the signal input. This implementation is strong and has low cost, with potential applications for real time pattern recognition.

In this work we propose a generalization of the convolution kernel capable of realizing image processing operations as edge enhancement, phase visualization, image restoration, by using a joint transform correlator. The proposal convolution kernel is designed according to the operation to be performed. We present numerical simulations for each convolution kernel which performs the corresponding operation. On the other hand, experimental results are presented from the optical implementation of the convolution kernel by using a joint transform correlator which has the advantage of avoiding alignment difficulties presented by classical Fourier processors.

A cerebral aneurysm is a weakened portion of an artery in the brain. When a cerebral aneurysm ruptures, a specific type of bleeding known as a subarachnoid hemorrhage (SAH) occurs. No test exists currently to screen people for the presence of an aneurysm. The diagnosis of a SAH is made after an aneurysm ruptures, and the literature indicates that nearly one-third of patients with a SAH are initially misdiagnosed and subjected to the risks associated with aneurysm re-rupture. For those individuals with a suspected SAH, a computerized tomography (CT) scan of the brain usually demonstrates evidence of the bleeding. However, in a considerable portion of people, the CT scan is unable to detect the blood that has escaped from the blood vessel. For circumstances when a SAH is suspected despite a normal CT scan, physicians make the diagnosis of SAH by performing a spinal tap. A spinal tap uses a needle to sample the cerebrospinal fluid (CSF) collected from the patient’s back; CSF is tainted with blood after the aneurysm ruptures. To distinguish between a common headache and a SAH, a fast and an effective solution is required. We describe the development of an effective detection system integrating hardware and a powerful software interface solution. Briefly, CSF from the patient is aspirated and excited with an appropriate wavelength of light. The software employs spectrophotometric analysis of the output spectra and lays the foundation for the development of portable and user-friendly equipment for detection of a ruptured cerebral aneurysm.

In this paper, we introduce a novel method where several sensors and ATRs collaborate to recognize objects. Such an approach would be suitable for network centric application where the sensors and platforms can coordinate to optimize over all ATR performance. We use correlation pattern recognition techniques to facilitate the development of the concept, although other algorithms may be easily substituted. Essetnially, a self-configuring network is proposed that positions the sensors optimally with respect to each other depending on the algorithm and the class of the object to be recognized. We show how such a network optimizes overall performance, and illustrate the scheme by means of examples.

The growing sizes of the images as well as their complexities have reduced the competitiveness of the digital compression and multiplexing. These new requirements led the scientific community to look for new methods which will be adapted to these new demands. In this article, according to this objective, we propose and validate an all optical architecture implementing a new method of optical compression and mutliplexing. This method is based on a new technique of segmentation of Fourier plane (distribution of spectra in various zones according to a well defined criterion). This segmentation is aiming at neutralizing the redundant information appropriate for each sepctrum and multiplexing these verious spectra in the Fourier plane.